Tryfonas, T., & Beale, D. (2018). Exploration of the Complex Ontology.Paper presented at 28th Annual INCOSE International Symposium,Washington DC, United States.

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Exploration of the Complex Ontology

Dean Beale MSc., C.Eng., C.Phys., M.IET.

Dept. of Engineering

University of Bristol

Bristol, UK db15900@bristol.ac.uk

Dr. Theo Tryfonas PhD

Dept. of Engineering

University of Bristol

Bristol, UK theo.tryfonas@bristol.ac.uk

Copyright © 2018 by Dean Beale. Published and used by INCOSE with permission.

Abstract. The Oxford English Dictionary (OED), the established definition of words in the English

language, is at odds with other definitions of complexity proffered by Complexity Theory. This

variance is likely to cause confusion in the delivery community. The incorrect classification of a

project between ‘complicated’ and ‘complex’ is considered by some to be a major source of project

failure; resolving this issue is therefore critical. This paper explores the definition of complexity by

assessing definitions from various sources and by conducting a survey of over 100 delivery

professionals. The results demonstrate the extent of the confusion and have informed considerations

on how to resolve this. This paper recommends that it is essential that the definition is either defined

at the start, or that the term is avoided by using its components. This paper identifies a simple

modification to the OED definition that would resolve many of the issues, if implemented.

Introduction

Globalization and its associated information explosion mean that many delivery tasks are defined as

being complex. Consequently, delivery professions have risen to the challenge. The system

engineering profession prides itself on its ability to handle complex delivery tasks. In project

management, agile methodology has been developed, to a considerable extent, to accommodate

modern complex delivery requirements [1]. ‘Complex’ and ‘complexity’ have also become

buzzwords that justify significant further investments, an individual’s recognition, and the selection

of alternative approaches to delivery.

Despite this global-scale response to the rise of complexity, the term ‘complex’ itself is poorly

defined. This causes significant confusion. The term is often referred to as being difficult to define

[2]. Some have stated that one will know that something is complex when one sees it [3]. Meanwhile,

others stick to the dictionary definition, treating it at best as a synonym of ‘complicated’, which, for

many in the delivery community, is almost the antithesis of ‘complex’. A potential reason for this

confusion is that aspects of the Complexity Theory definition are increasingly becoming established

in the minds of the delivery community, but not to the full extent and detail that these theories define.

Consequently, it is possible that different aspects of these theories and definitions are established in

different minds, including potential over-simplifications.

The challenge of being able to define complexity with clarity is reflected in the complexity tools that

have emerged. Many use titles to define categories of complexity that are unique to the tool; e.g. cow,

bull, horse [4], or wicked, messes, and wicked messes [5, 6]. Use of such terms appears to be the

byproduct of an immature lexicon to describe the types of difficulty or complexity being observed, or

a justifiable attempt to avoid contentious definitions. Some tools have ‘complexity’ in their heading,

axis and as an output, with different definitions for complexity being implied at each level without

explanation, confusing the reader and breaking category boundaries. Many simple project

categorization tools include ‘simple’, ‘complicated’, ‘complex’ and ‘chaotic’ [7, 8, 9, 10] as the

categories. Although these tools demonstrate support for there being a different meaning for a

complicated and a complex system, supporting Complexity Theory, they run contrary to dictionary

definitions for complex, complicated and chaotic, potentially having a profound impact on

maintaining the consistency of commonly accepted terms.

The absence of an agreed ontology has not gone unnoticed, and has led some to determine that there is

no rigorous definition [11] or that the term is user-specific. This lack of clarity suggests either that a

clear definition is impossible or that the current definition may not be complete.

If the definition of these terms was inconsequential then the confusion might be more acceptable.

However, it has been noted by Michael Cavanagh of The International Centre for Complex Project

Management that the misclassification of a project as a ‘complicated’ task rather than a ‘complex’

one was a major cause of project failure [12]. A plethora of stories support the importance of

understanding the difficulty and adjusting to it. For example, it was a change of approach to

accommodate complexity that enabled both NASA to get the first man to the moon, despite trialing

for many years prior, and for the US Army to defeat AQI in Iraq [13]. Consequently, it would appear

that not only is the definition uncertain, but also that this uncertainty could be a major cause of failure

for many substantial projects across the globe.

The purpose of this paper is to examine the ontology of complexity by looking at the definitions as

used by a range of sources in the hope that a clearer definition or understanding can be developed.

This paper will focus on the objective assessment of delivery complexity with the aim of supporting

the delivery practitioner in identifying complex tasks effectively. The expectation is to move the

definition of delivery complexity discussion along, rather than to finalize it.

Relationship to existing theory and work

It is worth stating at the outset that the authors’ understanding of complexity is historically from a

delivery perspective. As part of the literature survey, we draw on insights from Chaos Theory and

Complexity Theory and the insights that can be gleaned from Difficulty or Complexity assessment

tools. The authors specifically avoid discussing the vast range of definitions on complexity that

emerge from Complexity Theory in the many professional bodies and delivery approaches, instead

aiming to use the salient points that have come to the fore that can provide insights into what

definitions are most recognized by delivery professionals and therefore can be used to help determine

whether a task is complex or not.

Approach

The approach taken in this paper is to consider definitions of complexity and associated words as

derived from the following sources:

1) Dictionary definitions (Oxford English Dictionary [14]; Collins Dictionary [15]).

2) Definitions as implied by developed complexity, difficulty or risk assessment tools that

explicitly deal with uncertainty. There are many project management complexity assessment

tools that use ‘complexity’ as a synonym of ‘complicated’; these have been ignored for the

purposes of defining complexity, as they provide no value.

3) Generic definitions as implied by common mathematical theories.

The definitions will be compared, contrasted and analyzed so that a suitable range of options can be

identified for clarifying the definition of complexity and/or its associated terms. The associated words

to be examined in addition to complex are: difficult, complicated, chaos, chaotic, emergent and

uncertainty.

From this analysis, a survey is constructed that tests the prevailing view of over 100 delivery

professionals from both the public and private sectors. The results are presented and conclusions and

recommendations are drawn from the analyses and results.

Literature review

In describing the outputs of the literature review it is not possible to describe one element without

using definitions from other elements. Consequently, it is not possible to order these definitions such

that the reader can move from one definition to the next with a full understanding. Instead, all

definitions need to be read and understood to fully understand each one. Some terms are well defined,

but a discussion of all of them is required to put the definition of complexity into the right context.

The tables below are RAG coded. The table cell color indicates the alignment of the definition within

that source; the alignment column indicates the alignment between the different sources of definition.

For example, a definition can be aligned within all three sources of definition, but those different

sources can be at odds with each other. Red indicates disagreement between the definitions; amber

indicates inferred differences; green means largely aligned.

Difficulty:

Figure 1. Table detailing the definitions of ‘difficulty’ from dictionary, tools and mathematical

theories. The RAG color indicates the amount of alignment in definition.

Source Definition Alignment

Dictionary: OED: Needing much effort or skill to accomplish, deal with, or

understand.

COLLINS US: Hard to do, make, manage, understand, etc.; involving

trouble or requiring extra effort, skill, or thought.

COLLINS UK: Not easy to do; requiring effort; a difficult job; not easy

to understand or solve; intricate; a difficult problem; hard to deal with;

troublesome.

Tools Aligned to above.

Theories Not discussed.

This term is explored because of its ability to replace the use of the ‘complex’ term in the title of many

tools. Often tools are called ‘complex’, suggesting that they measure the amount of complexity in a

task. However, their output is typically ‘simple’, ‘complicated’, ‘complex’ or ‘chaotic’. This suggests

that they indicate that the amount of complexity as you move from ‘simple’ to ‘complicated’, to

‘complex’, and then to ‘chaotic’ is increasing. This can lead to confusion. One way to resolve this is

to use ‘difficulty’ as a measure/title instead. Difficulty is the amount of skill and/or effort required to

complete an activity. Classifying tasks as ‘simple’, ‘complicated’, ‘complex’ or ‘chaotic’ infers the

types and amount of skill or effort required to deliver the task.

Uncertainty:

Figure 2. Table detailing the definitions of ‘uncertainty’ from dictionary, tools and mathematical

theories. The RAG color indicates the amount of alignment in definition.

Source Definition Alignment

Dictionary: OED: Not able to be relied on; not known or definite.

COLLINS US: Lack of certainty; doubt; the state or condition of being

uncertain; an uncertain matter, contingency, etc. Definition of Certain:

Fixed, settled, or determined; sure (to happen, etc.); inevitable; not to

be doubted; unquestionable; not failing; reliable; dependable; unerring;

without any doubt; assured; sure; positive.

COLLINS UK: Positive and confident about the truth of something;

convinced; definitely known; sure; bound; destined; decided or settled

upon; fixed; unfailing; reliable.

Tools Sometimes synonymous with unfamiliarity (not know), sometimes

synonymous with unpredictability (not able to rely upon). Rarely are

both aspects of uncertainty treated. Often applied to the inputs of

system development (requirements and solution). The uncertainty of

the system that delivers tends to be treated in isolation.

Theories Output uncertainty is closely aligned with emergent behaviour.

‘Emergent’, however, is the space of unknown unknowns, whereas

uncertainty covers known unknowns as well.

Uncertainty is inherently related to complexity and chaos. Consequently, this term is popular as an

axis in delivery complexity tools. Typically, it is the unfamiliarity in the requirements (don’t know

what) and/or with the solution (don’t know how) [7, 8, 9] that is measured, as shown in Figure 3

below.

Figure 3. A representation of a simplified Stacy matrix [9] indicating the association of complexity

with uncertainty in the What (requirements) and the How (in this instance, technology), which is

synonymous with solution.

These tools are used as an indicator of uncertainty in the outcomes categorized as simple,

complicated, complex or chaotic, inferring that ‘complicated’ has a measure of uncertainty within it,

and that ‘complex’ is more uncertain, and hence more difficult, than ‘complicated’.

The challenge with the tools approach is that defining ‘complicated’ as containing ‘some uncertainty’

does not objectively fit the description in the OED or in Complexity Theory. However, it does fit

subjectively with how tasks and projects are delivered, in that complicated approaches can be used to

handle some uncertainty, and complex approaches are used to handle more uncertainty. The

challenge with this simplified view is that ‘uncertainty’ can readily be separated into uncertainty with

the current state (or familiarity) and uncertainty with the future state (unpredictability). The

uncertainty measured above appears to be associated with the familiarity of the task at the start; it

does not take into account the uncertainty during execution between the component parts

(unpredictability) of the system that makes the system (also known as the machine that makes the

machine, or M3) [16]. Typically, the M3 system is unpredictable due to human decision-making.

Both lead to unpredictability as to what the final product of the system to be made is (also known as

the machine to be made, M2M) [16] and how much uncertainty is inherent in that system.

This suggests that multiple types of delivery uncertainty exist that also need to be considered. These

can be considered collectively or in isolation, as described in Figure 4 below.

Figure 4. A table to indicate how input familiarity and system unpredictability combine to create

increasing levels of uncertainty in a system output.

Known and predictable

delivery system

Unknown or unpredictable

delivery system

Familiar with how

and what

1. Deterministic,

predictable outcomes

2. Uncertain outcome

Familiar with how

or what

3. Uncertain outcome 4. Highly uncertain outcome

Unfamiliar with

how and what

5. Highly uncertain

outcome

6. Extremely uncertain

outcome

Emergent (Emergence):

Complexity Theory, on the other hand, tends to discuss ‘emergence’ instead of the unpredictable

aspect of ‘uncertainty’. This term is popular in systems engineering. However, in the delivery

community, some confusion could arise between ‘uncertainty’ and ‘emergence’, from the

philosophical definition of ‘emergence’ as used in Complexity Theory, and the more commonly

understood meaning, which is aligned to the Middle English or US definition (see Figure 5 below).

Figure 5. Table detailing the definitions of ‘emergent’ from dictionary, tools and mathematical

theories and other sources. The RAG color indicates the amount of alignment in definition.

Source Definition Alignment

Dictionary: OED: 1. In the process of coming into being or becoming prominent. 2.

Philosophy (of a property) arising as an effect of complex causes and

not analysable simply as the sum of their effects. 3. Middle English:

Occurring unexpectedly.

COLLINS US: Arising unexpectedly or as a new or improved

development; recently founded or newly independent.

COLLINS UK: Coming into being or notice; (of a nation) recently

independent.

Tools If discussed, more in terms of OED 3 or COLLINS US above (arising

unexpectedly).

Theories Emergence often discussed in Complexity and Chaos Theories as

defined in OED definition 2 above.

Other The whole is more than the sum of the parts, non-linear. [11]

Emergence in Complexity Theory differs from uncertainty in that it is focused around the unknown

unknown aspects of the outputs (predictability), whereas uncertainty covers the known unknowns and

the unknown unknowns of both familiarity and predictability. As such, it is either a subset of or a

synonym for ‘unpredictability’, depending on which OED definition is used.

Subjectively, however, an inability or unwillingness of the observer to analyze what the sum of the

effects of a system is means that it will often not be possible to separate the terms. As Complexity

Theory thinking, and hence the term ‘emergence’, permeates the thoughts of the delivery community

without proper introduction, there is a risk of confusion between the US/Middle English term

(unpredictability) and the philosophical term favored by Complexity Theory (unknown unknowns).

In addition, both the M3 and M2M system can exhibit philosophical emergence in addition to the

unpredictability that can be caused by the known unknowns.

Complicated:

The definition of complicated is universally agreed upon across dictionaries and in mathematical

theories as consisting of ‘many interconnecting parts or elements; intricate’. All definitions notably

exclude any reference to uncertainty.

Figure 6. Table detailing the definitions of ‘complicated’ from dictionary, tools and mathematical

theories and other sources. The RAG color indicates the amount of alignment in definition.

Source Definition Alignment

Dictionary: OED: Consisting of many interconnecting parts or elements; intricate.

Antonym = Easy, simple, straightforward.

COLLINS US: Made up of parts intricately involved; hard to untangle,

solve, understand, analyze, etc.

COLLINS UK: Made up of intricate parts or aspects that are difficult to

understand or analyze.

Tools Some tools infer [7, 8, 9, 10] that complicated systems have some

uncertainty. Others assume no uncertainty [16].

Theories Generally discussed as the absence of uncertainty.

In Complexity Theory, the definition of an intricate system without uncertainty is complicated. So

‘complicated’ is strictly defined as not having uncertainty. The dictionary makes no reference to

uncertainty. This is important because the dictionary description of ‘complex’ infers or states that it is

a synonym of ‘complicated’. As discussed above, some tools, such as those shown in Figure 1,

indicate that there is some uncertainty in complicatedness. It is assumed that these tools are using the

subjective delivery definition, which accommodates the fact that complicated delivery tools are able

to cope with some uncertainty, as demonstrated by the importance of risk logs. Indeed, it can be

argued that the greater the skill of the practitioner, the more uncertainty he or she can handle using

tools designed for a largely complicated task.

Chaos (Chaotic):

Figure 7. Table detailing the definitions of ‘chaos’ from dictionary, tools and mathematical theories

sources. The RAG color indicates the amount of alignment in definition.

Source Definition Alignment

Dictionary: OED: 1. Complete disorder and confusion. Antonym = Order. 2. The

property of a complex system whose behaviour is so unpredictable as to

appear random owing to great sensitivity to small changes in

conditions. Chaotic systems that exhibit either 1 or 2 above.

COLLINS US: 1. Extreme confusion or disorder. 2. Ancient

Mathematics: a pattern or state of order existing within apparent

disorder, as in the irregularities of a coastline or a snowflake.

COLLINS UK: Complete disorder; utter confusion.

Tools Significant uncertainty in the requirements and solution of a task that

combine to create chaotic outcomes. A combination of high

unpredictability, intricacy and unfamiliarity that means that the outputs

are unlikely to be aligned to expectations.

Theories

Chaos Theory: A system that appears random due to the high

sensitivity of the input parameters, although in actual fact the system is

deterministic and hence repeatable if the exact same inputs are used.

Otherwise it appears random.

Complexity Theory: Chaos is an extreme form of complexity; i.e.

highly emergent.

Chaos Theory definition requires absolute predictability in the system. As such, it falls outside the

Complexity Theory definition of a complex system, which mandates unpredictability or the

non-deterministic nature of the system. This Complexity Theory definition does include chaotic

systems that are non-deterministic. A chaotic system produces outputs that are so unpredictable, even

if repeated exactly, that they seem unrelated with the inputs. This is treated as a subset of a complex

system where the unpredictability or emergence is extreme. A Chaos Theory system, however, only

emulates this system, while it is in fact a deterministic system and hence is repeatable. Consequently,

the Chaos Theory definition does not match the dictionary definition of chaos as a subset of a

complex system, or as a system with complete disorder and confusion. However, the OED definition

of chaos uses terminology that indicates that it directly references Chaos Theory, albeit notably minus

the deterministic clause. Consequently, it appears that the definition of chaos in the OED responds to

the Complexity Theory definition of emergence, but actually uses unpredictability instead.

The prevalent use of ‘unpredictability’ suggests that a soft or adulterated form of Complexity Theory

definition is being established where ‘unpredictability’ replaces ‘emergence’, and where many of the

other aspects of Complexity Theory definition, such as context and history-specific and feedback

loops are simplistically folded into the ‘unpredictable’ banner. One could consider this a ‘soft’

Complexity Theory definition.

An example of this in the tools, as illustrated in Figure 3 above, is where chaos is defined as

significant uncertainty (unfamiliarity) in the requirement and solutions space [a], where a complex

system shows only some uncertainty (unfamiliarity) in these two elements. This indicates that a

chaotic system is an extreme form of a complex system with more uncertainty (unfamiliarity), and

that the definition of ‘chaotic’ as an extreme form of ‘complex’ aligns to all definitions. However,

chaotic and complex systems focus on the unpredictability or emergence in the system, not the

familiarity discussed in these tools.

Complex:

Figure 8. Table detailing the definitions of ‘complex’ from dictionary, tools and mathematical

theories and other sources. The RAG color indicates the amount of alignment in the definition.

Source Definition Alignment

Dictionary: OED: Consisting of many different and connected parts; not easy to

analyse or understand; complicated or intricate. Antonym = Simple or

straightforward.

COLLINS: Consisting of two or more related parts; not simple;

involved or complicated.

Synonym note: ‘complex’ refers to that which is made up of many

elaborately interrelated or interconnected parts, so that much study or

knowledge is needed to understand or operate it [a complex

mechanism]; ‘complicated’ is applied to that which is highly complex

and hence very difficult to analyze, solve, or understand [a complicated

problem]; ‘intricate’ specifically suggests a perplexingly elaborate

interweaving of parts that is difficult to follow [an intricate maze];

‘involved’, in this connection, is applied to situations, ideas, etc. whose

parts are thought of as intertwining in complicated, often disordered,

fashion [an involved argument]. The opposite of ‘complex’ is ‘simple’.

Tools

Some uncertainty in the requirements and solution of a task [7, 8, 9,

10]. Complex is a task with considerable uncertainty, which is however

possibly manageable using the right approaches by acceptance and

embracing of that uncertainty as in Agile delivery methods. Intricacy

and unfamiliarity in the task are sufficiently high that unexpected or

emergent outcomes may arise [db]. It is considered much more

challenging to handle than complicated systems. Cynefin definition

[17] reflects Complexity Theory definition.

Theories Difficulty to define, but inconclusively specified as a system that

exhibits:

1. Emergence (see above).

2. Is non-deterministic.

3. Has feedback and hence is able to resist or amplify change (is

self-healing as in rainforests).

4. Not necessarily complicated (intricate).

The opposite of complexity is clarity.

Other A complex system exhibits emergence [11]. The whole is different

from the sum of the parts, history matters, sensitive to context,

emergent, episodic (activity in fits and starts) [boulton].

Project managers characterize it as complicated + uncertainty [2],

adaptive systems, self-organization & emergence [2].

‘Complex’ as defined in dictionaries is essentially a synonym of ‘complicated’, with its opposite

being ‘simple’ (Collins). The dictionary definitions are closely aligned. However, the Complexity

Theory definition is also mature, although notably not finalized, and agreed across many

communities. These two definitions are at odds with each other. This is most obvious when looking at

the Synonym note in the Collins dictionary, which explicitly states that ‘complicated’ is a more

challenging form of ‘complex’; i.e. ‘complex’ is hard to understand and ‘complicated’ is very hard to

understand. This directly contradicts the delivery community’s understanding and tools usage of the

term.

Many delivery methods for handling complexity are aligned closely to the Complexity Theory

definition in that it has emergence or unpredictability as a key element. However, this alignment often

does not go down to the exact description of ‘complex’ as described by Complexity Theory. In

particular, tools and methods appear to use a soft form of ‘complex’ as specified by Complexity

Theory in that ‘emergent’ is synonymous with ‘unpredictability’ in the round.

Consequently, tools are roughly aligned to Complexity Theory, but Complexity Theory is in

complete disagreement with both dictionaries, particularly Collins. As the difference between these

definitions leads to different delivery methods, this is critical to resolve or clearly understand at least

from a delivery community perspective. It has already been mentioned that the misclassification of a

project as ‘complicated’ instead of ‘complex’ is considered by some the main source of project failure

[2]. The confusion caused by the use of an alternative definition throughout much of the delivery

community to that used in dictionaries can only exacerbate the issue.

Analysis

As can be seen, based on current definitions, it is not possible to resolve the definitions of complexity,

chaos and complicated systems without breaking one of the associated OED definitions, and/or

stepping out of line with the developed theories. Either these issues need to be resolved or the full

ambiguity of these terms needs to become more commonly understood and communicated for clear

discussions around complexity to take place.

By analyzing all the terms reviewed above it is hoped that one or more suitable solutions to resolving

the definition of complexity can be identified, around which the community might coalesce.

Summary of the issues

Before we start the analysis it would be valuable to summarize the issues.

1) Dictionary definitions are not aligned: ‘Chaos’ is defined as ‘a complex system whose

behaviour is so unpredictable as to appear random owing to great sensitivity to small changes in

conditions’. This suggests that a complex system typically exhibits unpredictable behaviour, and that

a chaotic system is an extreme case of this. The definition of ‘complex’ is synonymous with

‘complicated’, with no reference to unpredictability. Collins Dictionary goes a step further and

suggests that a ‘complex’ problem is easier to deliver than a ‘complicated’ problem. These definitions

seem to contradict one another.

This issue can also be considered by looking at the opposites. The definition of chaos indicates that a

complex system has unpredictability; hence the opposite would be ‘predictability’. The definition of

complex indicates that the system is intricate; the opposite is ‘simple’ or ‘straightforward’, as is the

case for ‘complicated’.

In addition, the definition of emergence, a form of uncertainty, indicates that it arises from a complex

system. It appears that Complexity Theory definitions have been identified in some terms within the

dictionary, but not in the complex or complexity terms.

2) Dictionary and Complexity Theory definitions of complex are not aligned: Complexity as

defined in the dictionary does not align to the Complexity Theory definition. The increasing

pre-eminence of Complexity Theory means that this clash should not be ignored. It is possible that the

emergence of Complexity Theory ideas among delivery community members who have not

otherwise studied it is causing the confusion. However, it appears that the soft form of ‘complex’ as

defined in Complexity Theory is emerging, in part because it is not possible to define ‘complex’ as in

Complexity Theory properly in less than a page or two, and that the definition is itself contended.

3) Chaos Theory is not a complex system: Complexity Theory states that a complex system is

emergent: the sum total of its parts cannot be used to predict its outcome; i.e., it is not deterministic. A

Chaos Theory system is specifically a deterministic system where the sum total of all its parts can be

used to predict its behaviour, but due to the hyper-sensitivity of the inputs it looks like a complex

system. It is explicitly a counterfeit complex system. This means that in the description of ‘chaos’ the

OED references a complex system, but largely uses the definition of a Chaos Theory system, minus

the term ‘deterministic’. The absence of this term means that one must assume a complex system even

though the terminology infers a Chaos Theory system. This first description of complete or extreme

disorder or confusion aligns well with Complexity Theory definitions as chaos as an extreme form of

complexity that has emergent (or unexpected outcomes).

Survey structure

To further analyze the definition of complexity as observed by the delivery community, a survey was

constructed based on the above discussion. The focus of the survey was to:

1) identify what definitions were most recognized by the professional delivery community and

consequently determine how best to communicate and discuss complexity and its associated

terms.

2) determine to what extent the Complexity Theory definition had permeated this community in

hard or soft form.

To achieve this, the dictionary definitions, along with definitions that reflected both the hard and soft

forms from Complexity Theory, and the tool definition inferred by Figure 1, were presented to over

400 delivery professionals in the public and private sectors, with over 100 responses split between

system engineers and project managers. The questions asked were:

Question 1) Please indicate in order of preference [1, 2, 3, etc] these definitions of system complexity

that you agree with. If you disagree, please indicate with a ‘d’.

a. Consisting of many different and connected parts, not easy to analyze or understand,

complicated, intricate.

b. Consisting of parts where the whole is different (greater or less) from what could be

determined by the sum of the parts, exhibiting feedback mechanisms, where the

outcome is also dependent on the context and history.

c. Consisting of many different and connected parts, not possible to fully analyze or

understand, leading to uncertainty in the outcome.

d. Consisting of any elaborately interrelated or interconnected parts, so that much study

or knowledge is needed to understand or operate it [a complex mechanism]; whereas

complicated is applied to that which is highly complex and hence very difficult to

analyze, solve, or understand [a complicated problem].

e. A system/task where some uncertainty in the requirements and the solution makes it

difficult to deliver, where more uncertainty in the requirements and the solution would

make it chaotic to deliver and less uncertainty would make it complicated.

f. Other: Please specify______________________________________________

Answer (a) is the OED definition of complexity. Answer (b) reflects the Complexity Theory

definition in a few words using key principles. As noted above, these definitions typically take many

paragraphs, so any attempt to condense them will be considered a poor imitation. The use of a fuller

definition was considered prohibitive to being able to conduct the survey; consequently, the aim was

to be close enough. The answer purposely does not use the term ‘emergent’; instead, the definition of

emergent was used. The reason for this, as discussed above, is that the definition of emergent is

ambiguous too; therefore we used the Complexity Theory definition of emergent to reduce confusion.

Answer (c) is an extended OED version and was designed to test the acceptance of a soft version of

complexity, as discussed above, with minimal change. Again how best to do this is not readily

obvious and is subject to interpretation; however, it only needed to be close enough to indicate the

intention. Answer (d) is a clarifying note in the Collins Dictionary. Answer (e) was designed to reflect

the diagrams used in delivery methodologies to determine whether a task is complex or not, as shown

in Figure 3. It is useful to see whether the Figure diagram, which is often presented and readily

accepted, was equally accepted when written down in text, forcing a more objective response.

Answer (f) was used to check that no obvious definition had been missed.

A second question was also asked.

Question 2: Please indicate the level of difficulty associated with the following words [1 = not

difficult; 4 = most difficult]: complex, chaotic, simple, complicated.

This question was asked to check the validity of the assumption that ‘complex’ is considered more

difficult than or equally difficult to ‘complicated’, a principle supported by all the definitions, as

illustrated in Figure 3, apart from the Collins note, which suggests that ‘complex’ is less difficult.

This question can also be used to check whether respondents had read the Collins definition correctly,

as it is possible for the answer to question 2 and Collins Dictionary to contradict each other. In

addition, the survey was introduced as a one-minute activity; however, the Collins note is considered

by the authors to be too complicated for a quick survey. Observation of the contradiction can be used

to indicate whether the respondents were using their intuition (or system 1) or their logical thinking

(system 2) [18] to respond to the survey.

Results

The results to question 1 of the survey are shown below in Figure 9. To assess the level of alignment

to each definition, the top two preferred definitions of each respondent were summed and compared

to the number of respondents who disagreed with the same definition.

Figure 9. A graph to indicate the number of respondents who selected each definition within the top

two preferred definitions of complexity and the number of respondents who indicated that they

disagreed with the same definition.

It can be seen from Figure 9 that the tools that are accepted subjectively are largely rejected when

assessed objectively. This does not mean they are not useful subjectively, however. The Collins note

is also highly controversial. The most relatable definitions, the OED and the extended OED, however,

still had more than 10% of the respondents directly disagreeing. This indicates confusion and a lack of

alignment of the definitions across the delivery community.

The results can also be analyzed via both community and sector, as shown in Figure 10 below.

OED ComplexityTheory

ExtendedOED

Collins Note Tools

53%

39%

57%

26%20%

11%15% 13%

24%29%

Responses from all communities

Top 2 preference Disagree

0%

10%

20%

30%

40%

50%

60%

70%

Public Sector responses

Top 2 preference Disagree

-10%

0%

10%

20%

30%

40%

50%

60%

70%

Private Sector responses

Top 2 preference Disagree

Figure 10. Graphs to indicate the number of respondents who selected each definition within the top

two preferred definitions of complexity and the number who indicated that they disagreed with the

definition, from the public sector, private sector, project management and systems engineering

communities.

Both private- and public-sector communities showed similar support for the OED definition. The

difference appears to be the acceptance of the Complexity Theory definition. The private sector

preferred the full Complexity Theory definition, while the public sector strongly preferred the

extended OED version. Comparing the systems engineering and project management communities,

the acceptance of the Complexity Theory definition is again the prevailing difference: the systems

engineering community supported it in first place, while the PM community ranked it in fourth place.

These results indicate strong community differences within the delivery community on terms that

they related to.

About 10% of the respondents provided alternative definitions. Many of these were alternative forms

of the Complexity Theory definition, such as the INCOSE or Cynefin [17] definitions. Some

provided added clarity to the extended OED definition with the addition of uncertainty with the inputs

or familiarity of the system. These responses, principally from system engineers, support the

hypothesis that producing effective definitions including Complexity Theory concepts is challenging.

A few genuinely new approaches to defining these terms were also proposed that were insightful, and

could be a better starting point for the definition of complexity. However, there is a concern that

increasing the number of competing definitions may cause more issues. The challenge is that, despite

many having strong views on what the definition is, these views are not typically the views of others.

In response to question 2, 38% provided responses that disagreed with ‘chaotic’ being more difficult

than ‘complex’, ‘complex’ being more difficult than ‘complicated’, and ‘complicated’ being more

difficult than ‘simple’. 17% of respondents explicitly indicated that a ‘complex’ task was easier to

deliver than a ‘complicated’ task, supporting the Collins note, but countering many of the definitions

of ‘complex’. This result is surprising and again underlines the importance of avoiding confusion.

44% of respondents’ answers to question 2 and question 1(e) conflicted, suggesting that the short

timeframe associated with the survey drove a system 1 intuitive assessment.

-10%

0%

10%

20%

30%

40%

50%

60%

70%

Systems Engineering responses

Top 2 preference Disagree

0%

10%

20%

30%

40%

50%

60%

70%

Project Management respnoses

Top 2 preference Disagree

Discussion

The results above indicate that there is significant opportunity for confusion around the definition of

key terms, especially across communities. It suggests that the misclassification of a project as

complicated rather than complex could readily be achieved due to misunderstanding the definition of

a complex system.

In order to communicate more effectively when we discuss complex systems we need to either: 1)

define what we mean each time with each audience; 2) avoid the term altogether, perhaps using

component parts such as intricacy, unfamiliarity and unpredictability [16] and how they contribute

towards making it difficult; or 3) align the definitions.

Option 1 above fails when the ‘local’ definition is consistently reinforced. Consequently, option 2 is

the most suitable approach short term. Option 3 is a longer-term approach with four options:

a) Keep the OED definition.

b) Support and wait for the Complexity Theory definition to establish itself.

c) Extend the OED version to accommodate uncertainty.

d) Propose a new definition.

Option a) is still largely the current state. This approach is being eroded by Complexity Theory

definitions; this needs to be reflected in the OED definitions.

Option b) defining complex as in Complexity Theory (hard) typically takes many paragraphs to

explain, and even then it is recognized as not fixed, complex and elusive. Consequently, a commonly

understood definition is likely to be evasive, even as the definition is established, unless it is

substantially simplified.

Option c) has significant benefits, although it does not solve all the problems. Adding uncertainty or

unpredictability to the OED definition supports the soft form of Complexity Theory definition and

would allow the hard form to co-exist with the modified OED version. It essentially unifies the space

with only a minor amendment. It resolves all three issues listed above, fixes the implied difference

between the OED definition of ‘chaos’ and ‘complex’, and allows Chaos Theory to be considered a

complex system, even though it is a unique case. The survey also suggests that the extended version is

the most acceptable definition to delivery professionals.

Option d) is appealing; however, this approach, without any globally authority establishing it, would

allow a swathe of competing strongly held definitions to propagate, exasperating the Complexity

Theory challenges in seeking consensus, and ensuring that the other person understands you further.

Conclusions and recommendations

It can be concluded from this work that, despite the importance of understanding what a complex

system is so the difficulty can be handled and mitigated effectively, the definition of complexity is

confused both in literature and in practice. It can be concluded that, in the short term, delivery

professionals should seek to avoid using the term as it can cause confusion. When selecting delivery

approach elements it should be achieved by assessing the system to identify those aspects that lead to

difficulty in delivering customer requirements and identifying techniques that mitigate those

difficulty aspects.

In the long term, a range of options has been considered. It is concluded that the only option that

appears to resolve the issues in the definition of complexity is to extend the dictionary definitions to

include aspects of uncertainty; for example, unfamiliarity and unpredictability in the system or its

inputs, leading to unpredictability in the outcome.

Further work

The definition of uncertainty, unpredictability, and emergence in the M2M, M3 inputs, system and

outputs should be explored further than this paper has been able to.

In addition, it has been identified as part of this work that Chaos Theory and Complexity Theory share

references to sensitivity and determinism or unpredictability. Examination of the

determinism-sensitivity space in which both these definitions sit could also prove beneficial.

Acknowledgements

The authors would like to acknowledge the many conversations with delivery professionals and staff

across public- and private-sector organizations, Bristol University and at international conferences

for helping with the exploration of the definitions of these terms. The authors would also like to thank

those who took time to fill out the questionnaire to support the survey results.

References

[1] Scrum alliance from: www.scrumalliance.org/why-scrum

[2] Hass, K., 2009, ‘Managing Complex Projects A New Model’, Management Concepts Inc.

[3] Know it when you see it quote. [need to complete the ref]

[4] Little, T., 2005, ‘Context-Adaptive Agility: Managing Complexity and Uncertainty’, xxx [need to

complete the ref]

[5] Grint, K. clinical leader, 2008, ‘Wicked Problems and Clumsy Solutions: The Role of

Leadership,’ British Association of Medical Manager (BAMM), vol. I, no. II.

[6] Wicked messes paper. [need to complete the ref]

[7] Obeng, E., 2012, ‘World after Midnight,’ TED talks.

[8] Turner, J., Cochrane, R.,1993, ‘Goals-and-methods Matrix: Coping with Projects with Ill-defined

Goals and/or Methods of Achieving Them,’ International Journal of Management, Vol. 11(2),

pp. 99–102.

[9] Stacy, R., 2012, Tools and Techniques of Leadership and Management, Routledge.

[10] Snowden, D.J., Cognitive Edge. [need to complete the ref]

[11] Holland, J., 2014, Complexity – A very short introduction, Oxford University Press.

[12] Cavanagh, M., 2013, ‘Project Complexity Assessment’, ICCPM, Kindle.

[13] McChrystal, General S. (retired), 2015, Team of Teams, Penguin, UK.

[14] Oxford University Press, 2004, The Dictionary of English.

[15] Collins dictionary reference. [need to complete the ref]

[16] Beale, D., Young, M., 2016, ‘Initial Thoughts on Measuring and Managing Complexity’,

European TEMS Symposium.

[17] Snowden, D.J., Boone, M.E., 2007, ‘A Leader’s Framework for Decision Making’, Harvard

Business Review.

[18] Kahneman, D., 2011, Thinking Fast and Slow, Penguin Books, UK.

Biography

Dean Beale has spent his career, principally within QinetiQ, delivering complex and difficult projects

in the defence and security sector serving a variety of Government customers. These roles have

included; Technical Manager, Project Manager and Systems Engineer. Dean has published over 20

papers in his fields of interest and was a Visiting Lecturer at the University of Birmingham on Project

Management. Dean is currently studying a Ph.D in ‘Assessing complexity and difficulty in

organizational change with associated mitigation strategies’ at the University of Bristol.